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An NER-based Product Identification and Lucene-based Product Linking Approach to CPROD1 Challenge Description of Submission System to CPROD1 Challenge
Conference proceeding

An NER-based Product Identification and Lucene-based Product Linking Approach to CPROD1 Challenge Description of Submission System to CPROD1 Challenge

Zhiqiang Toh, Wenting Wang, Man Lan and Xiaoli Li
12TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2012), pp.869-871
International Conference on Data Mining Workshops
01/01/2012

Abstract

Computer Science Computer Science, Artificial Intelligence Computer Science, Information Systems Science & Technology Technology
This paper presents our methodology for CPROD1 Challenge, which is to identify the product mentions from text and then link the product to the entries in the catalog file. Our solution follows 2 steps. First, we use processing pipelines to extract product mentions by incorporating multiple techniques including traditional named entities recognition (NER), regular expression rules and gazetteer-based string matching. Second, we view product linking task into an information retrieval (IR) problem, where the description catalog file is populated into a database. Thus, each product mention acts as a search query and the returned results from catalog entry database serve as the links. The F1 scores of our submission on public and private test data are 24.82% and 16.04%, respectively.

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